Workflow System and Method for Single Call Batch Processing of Collections of Database Records

ABSTRACT

A system and method of processing a flow of information may include capturing information for use by a workflow system, the information including internal content that is internal to the workflow system and external content that is external to the workflow system. The method may further include analyzing the internal content and the external content to determine metadata parameters for the captured information; associating the captured information with a process based at least in part on the metadata parameters; processing the captured information in accordance with the process associated therewith to thereby produce output data; formatting the output data into formatted output that conforms to an external system communicatively connected to the computer, the external system having fidelity and quality requirements for a delivery method; and delivering the formatted output to a recipient using the delivery method.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.11/486,398, filed Jul. 12, 2006, entitled “WORKFLOW SYSTEM AND METHODFOR SINGLE CALL BATCH PROCESSING OF COLLECTIONS OF DATABASE RECORDS,”which claims priority to U.S. Provisional Patent Application No.60/698,678, filed Jul. 12, 2005, entitled “COMPLEX DATA MERGING, SUCH ASIN A VECTOR-BASED WORKFLOW APPLICATION,” and U.S. Provisional PatentApplication No. 60/698,700, filed Jul. 12, 2005, entitled “WORKFLOWSYSTEMS.” All applications listed in this paragraph are incorporated byreference herein in their entireties.

BACKGROUND

Workflow technologies are often used to manage and monitor businessprocesses. For example, workflow technologies allow users to efficientlydefine and track processes that involve work spanning multipleindividuals and/or departments within an organization (or even acrossorganizations). Existing workflow technologies often allow users toautomate a range of tasks, which are often dependent on large amounts ofspecific information. Accordingly, executing a task may involveperforming functions (sometimes repeatedly) on large sets of input data.

In general, tasks are created to perform a single or limited set offunctions and then combined with other tasks as part of largerprocesses. Some high-level examples of task functions include retrievingdata from a data store, retrieving data from an external application,sending data to a data store, sending data to an external application,reformatting input data to output data, transforming (computing) datafrom input to output, deriving new data from input data, relatingmultiple input streams of data with respect to each other, etc. As apractical example, workflow tasks may be responsible for notifyingemployees of pending work orders. Likewise, workflow tasks may enablemanagers to efficiently observe status and route approvals quickly.

Because the demand for workflow technology is high, there are many typesof workflow technologies on the market. Most workflow technologies aregenerally comprised of a package of several software components thatprovide functionality in areas of both workflow design and workflowexecution. In terms of workflow design, these software componentssometimes include workflow diagramming functionality having a workspaceor canvas used to create workflow diagrams (e.g., specify the placementof tasks and pipes, which define the sequence and flow of informationbetween tasks in a workflow). In facilitating workflow design, thesoftware components of workflow technologies often allow a user tospecify parameters and business rules to guide the flow of control, theflow of data, and the functions of tasks. In addition to facilitatingthe design of workflows, the software components of typical workflowtechnologies also facilitate the initiation, evaluation, and review ofworkflows (sometimes called “workflow models”).

In terms of executing workflows, typical workflow technologies includeprocessing capabilities that manage the flow of information along thepipes between tasks, apply business rules to direct the execution pathand data at pipe junctions, ensure data is passed as input to tasks,ensure user parameter metadata is provided to tasks, monitor andpropagate error status of the tasks and pipes, and save and restore jobcontext between sessions. However, existing workflow technologies areoften limited in the way that they execute tasks. For example, theytypically operate by reading input data one record at a time (with eachrecord limited to similarly shaped data), applying a task (function) tothe data, and outputting modified data after performing the task, onerecord at a time. In other words, in most workflow systems, each taskwithin a workflow inputs, processes, and outputs a single record priorto processing a subsequent record. In such systems, scalability isachieved by invoking parallel instances of a task, although eachinstance still incurs the individual memory and computational overhead.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing an example of an environment in whicha workflow facility having vector-based characteristics may beimplemented.

FIG. 2 is a block diagram showing an example implementation of asupporting architecture for implementing an embodiment of the workflowfacility.

FIG. 3 is a block diagram showing more general computing components thatcan be used to implement the workflow facility of FIG. 1 and thesupporting architecture of FIG. 2.

FIG. 4 is a data flow/block diagram showing aspects of assembling inputdata for use in a vector-based workflow facility.

FIG. 5 is data flow/block diagram showing aspects of assembling outputdata resulting from processing in a vector-based workflow facility.

FIG. 6 is a data flow/block diagram illustrating an example of joiningor merging data for use by a task of a workflow facility.

FIG. 7 is a flow diagram showing a high-level vector-based workflowprocess performed at the workflow facility.

FIG. 8 is a flow diagram showing a routine performed by a workflowaction utilizing vector-based data inputs to complete a step in aworkflow model.

FIG. 9 is a flow diagram showing a routine performed by an adaptermodule in performing processing in association with vector-based datainputs used to complete a step in a workflow model.

In the drawings, the same reference numbers identify identical orsubstantially similar elements or acts. To facilitate the discussion ofany particular element or act, the most significant digit or digits in areference number refer to the figure number in which that element isfirst introduced (e.g., element 204 is first introduced and discussedwith respect to FIG. 2).

A portion of this disclosure contains material to which a claim forcopyright is made. The copyright owner has no objection to the facsimilereproduction by anyone of the patent document or patent disclosure(including Figures), as it appears in the Patent and Trademark Officepatent file or records, but reserves all other copyright rightswhatsoever.

DETAILED DESCRIPTION I. Overview

A software system or facility allows for the efficient creation andmanagement of workflows and other customizable processes that define asequence of tasks or steps performed to reach a common goal (e.g., acommon business goal). Each of these tasks or steps is typicallydependent on information that the workflow application imports, derives,modifies, or exports. For example, to complete a task or step, theworkflow facility may access input needed to complete the task, performprocessing on the input (which may include applying rules, performingcalculations or data manipulations, or executing processes dependent onthe input), and then, where appropriate, produce an output relating tothe task or step (or possibly an output that may be used in completing asubsequent task or step).

Execution of a task or step may depend on the workflow facility havingthe capability to perform processing on multiple records for the purposeof creating new data for delivery as output. To further this purpose,the workflow facility described herein is configured to handle a singleinput unit comprising an entire collection (or vector) of records (inaddition to being able to handle input comprising only a single record).This vector-based record handling functionality is integrated into theinfrastructure of the workflow application architecture. For example,the workflow facility may invoke a workflow action in association withperforming a task or step. This single invocation of the workflow actionoperates within a runtime environment provided by the workflow facility.Because it is configured to access and work on vectors/collections ofrecords (as well as single records), only a single invocation of theworkflow action is needed to execute a task or step. This prevents theworkflow facility from incurring the overhead associated with invokingmultiple instances of a workflow action to complete a task or step thatrelies on a collection of records for its execution. Further, thevector-based design of the workflow facility does not require recodingor the like to achieve scalability.

Various components of the workflow facility, including components thatoperate within a runtime environment provided by the facility, performprocessing of the collection of records so that the step from theworkflow model can be completed. An example of such a component is anadapter module, which communicates with an invoked workflow action. Theadapter module may have both a data handling component (e.g., aconnector proxy) and a data processing component (e.g., a deviceconnector). In some embodiments, the data handling componentreceives/retrieves units of input (e.g., each comprising a collection ofrecords), receives metadata parameters, manages queues of processingrequests, and manages the parsing of a collection of records into a setof individual records. The data processing component performs aspecialized function/task on a given data set (e.g., a single record).

II. Example System Architecture

FIG. 1 is a block diagram showing an example of a system environment 100in which aspects of the workflow facility, which is configured forvector-based records handling, can be implemented. The systemenvironment 100 may include various components, thereby allowing theworkflow facility to perform various processes. Examples of suchprocesses may include information capture processes 102, informationanalysis processes 104, information processing processes 106,information formatting processes 108, information delivery processes110, etc.

The workflow facility's information capture processes 102 are used toretrieve information for use by the workflow facility in performingvarious actions. In particular, the workflow facility's informationcapture processes are equipped to handle vector-based input comprisingcollections of records. Such collections may typically be expressed inthe form of document schema written in XML. Table A below shows anexample of an XML schema for two XML documents. Table A is derived fromthe XML schema and record types fat each document. In this example,<invoices> and <users> are the record types, respectively. Each columnconforms to a specific record type derived from the XML schema for eachdocument.

TABLE A <invoices> <users>   <invoice>   <user>    UserID + Invoice dataUserID + Invoice data   </invoice>   </user>   <invoice>   <user>   UserID + Invoice data UserID + Invoice data   </invoice>   </user> .. . . . . </invoices> </users>

Table B below illustrates an XML output schema. The left-hand column ofthe table shows the output schema when the customer XML document is theparent document and the right-hand column of the table shows the outputschema when the invoices XML document is the parent. InvoiceData andUserData are the contents of the <invoice> and <user> elements,respectively. Such contents may themselves be elements or text,depending on the hierarchy described by the schema.

TABLE B User is the parent record Invoice is the parent record <user><Invoice>   InvoiceData   UserData   InvoiceData </Invoice>   . . .<Invoice> </user>   UserData <user> </Invoice>   . . . . . . </user> . ..

In some embodiments involving the merging of information from more thantwo input components that form hierarchical relationships, the workflowfacility identifies relationships among the input components havingcontents to be merged using a single root/parent document that defines atop-level sequence. In such cases, aside from the parent document, anysubsequent documents involved in the merge are directly or indirectlychildren of the parent. The children may define their relationships withonly their closest parent. Multiple children may share the same parent,but a child does not have a direct relationship with a grandparent. Toillustrate this using the XML documents from the example given in TableB, the customer information includes a city ID. The city information maythen be obtained from another XML document with city records (alsohaving a city ID field). However, in this particular example, thejoining of this information may be independent of the joining of theinvoice information with the customer information.

Other sample cases include the following: In the case where only oneinput is used, there is no join involved since the single document isthe root document. Where two documents are related purely by the orderof the records in the document, it may be possible to use an implicitkey relationship comprising the row number, even though the row numberis not an explicit field in either record. The workflow facility mayalso use literal/scalar values instead of collections where a value isreplicated as often as needed (e.g., a single message to be sent to allrecipients of a notification). Other samples of schema that may beproduced by the workflow facility are shown in Tables C and D below. Inparticular, Tables C and D show examples of XML that is passed from acustom action to an adapter (components of the workflow facility thatare described in more detail with respect to FIG. 2). Table C shows anexample of XML for a single input document.

TABLE C <|-- Single Input − Invoices as Document --><JobRequestParameters>  <OutputDestination>C:\folder</OutputDestination>  <ReportFormat>PDF</ReportFormat>   <OutputPrefix>FileName</OutputPrefix> </JobRequestParameters> <TaskParameters> <TaskParameter taskParameterID=“43493fecf”>   UserID + Invoice data </TaskParameter>  <TaskParameter taskParameterID=“63495fefa”>  UserID + Invoice data  </TaskParameter>  ... </TaskParameters>Table D shows an XML example of two input documents that have beenjoined.

TABLE D <|-- Merged Input − Invoices as Parent Document, Users as ChildDocument --> <JobRequestParameters>  <OutputDestination>C:\folder</OutputDestination>  <ReportFormat>PDF</ReportFormat>  <OutputPrefix>FileName</OutputPrefix> </JobRequestParameters><TaskParameters>   <TaskParameter taskParameterID=“83c93cecf”>  UserID + Invoice data + user data   </TaskParameter>   <TaskParametertaskParameterID=“13c93c6ce”>   UserID + Invoice data + user data  </TaskParameter>   ... </TaskParameters>

More generally, in performing information capture processes 102, theworkflow facility may identify and capture content from various inputsources 112 which may include common business applications (e.g.,systems such as Great Plains software, SAP applications, etc.). Examplesof content captured from the input sources 112 include documents 114,applications 116, and processes 118. In general, the workflow facilityis configured to capture both content that is internal to the workflowfacility and content that is external to the workflow facility and torepresent it in a form, such as an XML document schema, for processingby the workflow application.

The workflow facility's information analysis processes 104 are used tomanage and organize captured information so that the capturedinformation can be handled most appropriately by the workflow facilityduring processing. For example, in performing information analysisprocesses 104, the workflow facility may identify or categorize thecaptured content (e.g., identify it as a purchase order, an invoice,etc.) and then associate the content with an appropriate businessprocess. Accordingly, the information analysis processes 104 allow theworkflow facility to effectively handle a wide variety of content anddata. In some embodiments, the information analysis processes 104 areimplemented using one or more transformation engines 134 (shown as partof a supporting architecture 132), which perform processing associatedwith data analysis, data relationship rule application, sorting,filtering, data manipulation, etc.

The workflow facility's information analysis processes 104 are oftenfollowed by processing processes 106. The processing of captured contentusing the processing processes 106 may include transforming aspects ofdata from the captured content into a standard format such as XML. Asdescribed in more detail with respect to FIG. 2, when dealing withvector-based inputs (e.g., collections of records vs. single records),the processing processes may be implemented, at least in part, via theuse of one or more adapter components. In some embodiments, theprocessing processes 106 are implemented using one or more adapters 136(shown as part of the supporting architecture 132).

To allow delivery of different types of output to different types ofsystems, output resulting from the processing processes 106 may beformatted by one or more formatting processes 108. For example, theformatting processes 108 may use a template approach to format outputdata so that it conforms to an external system or so that it meetsfidelity and quality requirements for a particular delivery method to beused.

The workflow facility may rely on delivery processes 110 that allowformatted output to be delivered to an intended recipient. Such deliveryprocesses 110 may be associated with various delivery methods (e.g.,fax, email, print, web (HTML, XML), Wireless (SMS for mobile devices),etc.) The delivery processes 110 may be configured to work withtechnologies capable of high-volume, simultaneous multi-channeldelivery, making communication with customers, partners, suppliers, andemployees more personalized and cost-effective. For example, onedelivery process may be associated with automatically sending out largenumber of emails or faxes in single batches. In some embodiments,delivery may include delivery to a process or even delivery to a datastore.

The vector-based workflow processing performed by the workflow facility,which is described in more detail with respect to FIGS. 4-9, may rely ona combination of the processes described above (102-110). The variouscomponents that make up the workflow facility and enable it to performvarious processes, including the processes described above (102-110),include a delivery rules engine 128, a design environment 130, andvarious aspects of supporting architecture 132. For example, thedelivery rules engine 128 performs tasks associated with dataacquisition and identification, functional processing, outputpreparation, formatting, and delivery. Accordingly, the delivery rulesengine 128 may provide support for many of the processes associated withthe workflow facility, including intelligent routing between theinformation capture processes 102, the information analysis processes104, the information processing processes 106, the informationformatting processes 108, and the information delivery processes 110.Examples of different types of output data that result from the workflowfacility's processing processes 106 include documents 122, applications124, and processes 126.

The design environment 130 generally serves as an interface foradministrators of the workflow facility (including both softwaredevelopers and individuals with more basic programming skills). Forexample, the design environment provides various design, management,reporting, and administration tools/functionality. The features of thedesign environment 130 may enable developers to open an existing model,start with a blank model design canvas, or optionally use a predefinedmodel created externally (e.g., a Visio diagram) to start development.In this way, administrators can customize the workflow facility for theneeds of a particular organization. The creation of a workflow model mayinclude designing custom actions to be performed by the workflowfacility, designing custom end-user interfaces, and specifying custominput sources 112 and outputs 120. The design environment 130 may alsoprovide aspects of one or more end-user interfaces that are configuredfor users who do not have programming skills.

An underlying supporting architecture 132 provides a hardware andsoftware framework for implementing the facility. An exampleimplementation of the supporting architecture 132 is described in moredetail with respect to FIG. 2, which is a block diagram showing varioussample implementation details for the supporting architecture 132 ofFIG. 1. In particular, FIG. 2 focuses on aspects of the supportingarchitecture used during runtime while processing tasks usingvector-based inputs (collections of records).

One runtime-based component of the supporting architecture 132 includesa workflow action 202. The workflow action 202 may be implemented via asegment of executable code that, for example, runs locally in a serverspace provided by the workflow facility. The workflow action (e.g., adefault object called Task) is also sometimes extended by executablecode for a custom action or custom activity. In some embodiments, theworkflow action 202 is invoked by the workflow facility each time a stepneeds to be performed in association with a workflow model that theworkflow facility is currently executing/performing. The workflow action202 binds data (e.g., arguments) from existing input documents (e.g.,XML documents) to some type of formal input, such as an input schema. Inthe vector-based workflow system, these input documents comprisecollections of records (as opposed to single records used as inputs inmost workflow applications). The formal input (e.g., in the form of acollection of records) can then be used in association with the workflowaction 202 making a call to an adapter component 204 (or group ofadapter components), which performs the actual work associated with thestep from the workflow model. Communication between the workflow action202 and the adapters 204 can take place through a firewall 208. Thecommunication itself can be implemented, for example, using .Netremoting, with soap or Microsoft proprietary binary format, over TCP/IP.In an alternative embodiment, the adapter 204 may be exposed to theworkflow action 202 as a web service.

Each call to an adapter contains a job request comprising a collectionof task requests. Such task requests may specify operations to captureand bind documents to the workflow and to access the XML schema for suchdocuments. Both job requests and task requests have parameters (e.g.,composed of XML fragments). Accordingly, each adapter 204 is configuredto handle both jobs (collections of tasks) and tasks (individual tasks).Each adapter 204 may be specific to a designated function. Examples ofdifferent types of adapters 204 include adapters for data capture,adapters for report generation, and adapters for information delivery(e.g., email adapter, fax adapter, SMS adapter, etc.). In someembodiments, each adapter 204 is hosted inside a unique Windows service.For example, a Service Control Manager (SCM) can be used to start orstop each adapter process. Each adapter 204 has two primary components,a connector proxy/data handler 212 and a device connector/data processor214. The device connector/data processor 214 may be generic (i.e., thesame across all adapters associated with the facility) except that itincludes a unique task performer component 216, which provides thespecialized task-processing capabilities associated with each adapter204 (e.g., generate report vs. send batch email). The deviceconnector/data processor 214, through the specialized task performer216, is, thus, responsible for processing a specific type of individualtask one task at a time.

The connector proxy/data handler component 212 of the adapter isresponsible for processing all external requests at the job requestlevel and managing an adapter database 206. For example, when a jobrequest is received by an adapter 204, the connector proxy/data handlermay be responsible for initially causing a job request and associatedtask requests to be stored in the adapter database 206 upon receipt,fetching a next task request from the adapter database 206, and callingthe device connector/data processor 214 (which includes the specializedtask performer 216) to process a task when appropriate. In this way, thetask performer 216 may receive both job parameters and task parameterseach time a task is processed.

Because it is not itself required to conduct processing in associationwith specialized tasks, the connector proxy/data handler 212 may begeneric. The connector proxy/data handler 212 may also be responsiblefor composing the final job result (to be returned to the workflowaction) when all tasks for the job have been processed. In the meantime,the connector proxy/data handler 212 relies on the storage provided bythe adapter database 206 while performing a job, so that it can storeinformation as needed while the device connector/data processor 214performs tasks associated with a job prior to the time when theindividual task results can be compiled. In other words, job and taskresults may be stored in the adapter database 206 as they get computed,prior to being compiled and returned to the workflow action.

When more processing power is needed, a group of adapters 204 can beused to process task requests. In this case, all adapters 204 in thegroup point to the same adapter database 206. Load balancing occursbetween all adapters 204 in the group. In some embodiments, anadministrative user interface 210 enables managing adapters 204, adaptergroups, and adapter configurations.

FIG. 3 is a block diagram showing more general computing components thatcan be used to implement the workflow facility of FIG. 1 and thesupporting architecture of FIG. 2. Referring to FIG. 3, the generalcomputing components that can be used to implement the workflow facilityof FIG. 1 and the supporting architecture of FIG. 2 may include aspectsof a conventional computer 300, which includes a processing unit 302, asystem memory 304, and a system bus 306 that couples various systemcomponents including the system memory to the processing unit. Theprocessing unit 302 may be any logic processing unit, such as one ormore central processing units (CPUs), digital signal processors (DSPs),application-specific integrated circuits (ASIC), etc. Unless describedotherwise, the construction and operation of the various blocks shown inFIG. 3 are of conventional design. As a result, such blocks need not bedescribed in further detail herein, as they will be readily understoodby those skilled in the relevant art.

The system bus 306 can employ any known bus structures or architectures,including a memory bus with memory controller, a peripheral bus, and alocal bus. The system memory 304 includes random access memory (“RAM”)308 and read-only memory (“ROM”) 310. A basic input/output system (I/O)312, which can form part of the RAM 308, contains basic routines thathelp transfer information between elements within the computer 300, suchas during start-up. The hardware elements of the input/output system 312allow a user to enter commands and information into the computer 300through input devices such as a keyboard, a pointing device such as amouse, or other input devices including a microphone, joystick, gamepad, scanner, etc. (all not shown). These and other input devices areconnected to the processing unit 302 through an interface such as aserial port interface that couples to the bus 306, although otherinterfaces such as a parallel port, game port, or universal serial bus(“USB”) can be used. For example, other hardware devices, such as aPCMCIA reader that receives a card, can be coupled to the interface. Amonitor or other display device is coupled to the bus 306 via a videointerface, such as a video adapter. The computer 300 can include otheroutput devices, such as speakers, printers, etc.

The computer 300 also includes a hard disk drive 314 for reading fromand writing to a hard disk (not shown), and an optical disk drive 316and a magnetic disk drive 318 for reading from and writing to removableoptical disks 320 and magnetic disks 322, respectively. The optical disk320 can be a CD-ROM, while the magnetic disk 322 can be a magneticfloppy disk. The hard disk drive 314, optical disk drive 316, andmagnetic disk drive 318 communicate with the processing unit 302 via thebus 306. The hard disk drive 314, optical disk drive 316, and magneticdisk drive 318 may include interfaces or controllers (not shown) coupledbetween such drives and the bus 306, as is known by those skilled in theart. The drives 314, 316, and 318, and their associated computerreadable media, provide nonvolatile storage of computer-readableinstructions, data structures, program modules, and other data for thecomputer 300. Although the depicted computer 300 employs a hard disk,optical disk 320, and magnetic disk 322, those skilled in the relevantart will appreciate that other types of computer-readable media that canstore data accessible by a computer may be employed, such as magneticcassettes, flash memory cards, digital video disks (“DVD”), Bernoullicartridges, ROMs, RAMs, smart cards, nanotechnology memory, etc.

Program modules can be stored in the system memory 304, such as anoperating system 324 and other application programs 326, includingvarious aspects of the workflow facility such as those described withrespect to FIGS. 1 and 2. The system memory 304 may also include a webbrowser 328 for permitting the computer 300 to access and exchange datawith web sites in the World Wide Web of the Internet, as describedbelow. The application programs 326, including the workflow facility,may have access to one or more databases, which may be internal orexternal to the computer. For example, the workflow facility may haveaccess to a workflow database 330 (which stores designedworkflows/diagrams), a results database 332 (which stores results fromexecuted workflows), and multiple input source databases 334.

The computer 300 can operate in a networked environment using logicalconnections to one or more remote computers, such as a remote computer350. For example, the computer 300 may be involved in performing a firstset of tasks in a workflow, and the remote computer 350 may be involvedin performing a second set of tasks in the workflow. In another example,the remote computer 350 offers an input source for a workflow facilityhosted at the computer 300. Likewise, the computer 300 may be involvedin designing workflows having tasks to be performed by the remotecomputer 350. Like the computer 300, the remote computer 350 can be apersonal computer, a server, a router, a network PC, a peer device, orother common network node, and typically includes many or all of theelements described above for the computer 300. Typically, the remotecomputer 350 includes a memory storage device such as a disk drive 352.The remote computer 350 is logically connected to the computer 300 underany known method of permitting computers to communicate, such as througha local area network (“LAN”) 354 or a wide area network (“WAN”) orInternet 356. Such networking environments are well known in offices,enterprise-wide computer networks, intranets, and the Internet.

In a LAN networking environment, the computer 300 is connected to theLAN 354 through an adapter or network interface (not shown) coupled tothe bus 306. When used in a WAN networking environment, the computer 300often includes a modem or other device for establishing communicationsover the WAN/Internet 356. In a networked environment, program modules,application programs, or data, or portions thereof, can be stored in theremote computer 350, such as in the disk drive 352. Those skilled in therelevant art will readily recognize that the network connections shownin FIG. 3 are only some examples of establishing communication linksbetween computers, and other links may be used, including wirelesslinks. In general, while hardware platforms, such as the computer 300and the remote computer 350, are described herein, aspects of theinvention are equally applicable to nodes on a network havingcorresponding resource locators to identify such nodes.

III. Vector-Based Workflow System

The workflow facility may be implemented as a vector-based workflowfacility, where tasks can operate on more than one record at a time. Forexample, in a vector-based workflow facility, a single call to a datasource retrieves a collection of records for repeatable processing, asopposed to a single record. In this way, each computation task within aworkflow receives 0-N collections of records for processing as inputs atone time, and outputs 0-N records as output.

In some embodiments, the vector-based workflow facility further refinestasks as being comprised of two or more distinct components (e.g., adata handling component and a data processing component). For example, adata handling component may receive collections of data as input, managethe parsing of the collection of records into a set of single records,receive metadata parameters, manage queues of processing requests, andmanage multiple instances of a data processing component. Thus, ingeneral, the data handling component manages matters of scale for thevector-based workflow facility. On the other hand, the data processingcomponent may perform a function on a given set of data. In this way,the data processing component does not incur the overhead of invokingmultiple instances of a task. Instead, this responsibility is placed onthe data handling component, which invokes multiple instances of thedata processing component as needed.

FIG. 4 shows an example of a workflow iteration for a collection ofretrieved records. At block 401, the facility (and more specifically thedata handling component) reads in the input data one collection ofrecords at a time (i.e., as a single input unit). Details of an exampleof this process are illustrated and described with respect to FIG. 5.Additional examples are illustrated and described with respect to FIGS.7 and 8. At block 402, the facility applies a task to each record ofdata, prior to advancing to the next task. More specifically, the datahandling component may invoke one or more instances of a data processingcomponent to perform the task on each record in the collection. A moredetailed example of this data processing action is illustrated anddescribed with respect to FIG. 9. At block 403, the facility advances toapply the task to the next collection of records. Again, multipleinstances of a data processing component may be invoked to perform thistask. At block 404, the facility procures data output that results fromperforming the tasks. Details of an example of this process areillustrated and described with respect to FIG. 6, as well as FIGS. 7, 8,and 9. Like the data input, this data output may include a collection ofrecords (as opposed to a single record). At block 405, the facilityiterates over additional collections of records (if there is more thanone collection of records to be acted on).

As demonstrated in the above example, the vector-based workflow facilitysupports collections and/or sequences of input data (as opposed tosingle records) and, hence, executes sequences of tasks for eachinvocation of that task. For example, while a more typical workflowsystem executes a task to send one email to one recipient list, thevector-based workflow facility sends a sequence of emails, each to itsown recipient list. In other words, the vector-based workflow facilitysupports performing tasks with respect to sequences (including verylarge sequences). In this way, the vector-based workflow facilityenables efficiencies in workflows and supports very high throughputdelivery scenarios because the overhead of the workflow facility is keptto a minimum. The ability to identify and work on data that have commonattributes, as described herein, can be tied to the use of specificresources in the computing environment as well. Another embodiment orapplication of the vector-based workflow facility described herein wouldbe its use in conjunction with a simulation engine. The simulationengine may analyze a workflow application's overhead and/or identifypotential runtime bottlenecks resulting from anticipated data handling.The simulation engine may then use the results of the analysis to set athreshold value or otherwise suggest the need for the use ofvector-based operations to enhance system performance with workflowapplications that are used to handle large volumes of documents or thatperform operations on complex XML schema.

FIGS. 5 and 6 illustrate examples of actions performed by a vector-basedworkflow facility at runtime. For example, as illustrated in FIG. 5, insome embodiments, pre-processing occurs on input (e.g., XML input) tocreate a formal input document that a task may act on. Morespecifically, a joining and mapping functionality 508 may occur withrespect to a sequence of input documents (502, 504, and 506). Thejoining and mapping functionality 508 may involve collecting additionalinput 510 from existing workflow design or input documents in a workflowdesign store. Additional details of the joining and mappingfunctionality 508 provided by the facility in some embodiments aredescribed in more detail in commonly owned U.S. patent application Ser.No. 11/486,397, entitled “COMPLEX DATA MERGING, SUCH AS IN A WORKFLOWAPPLICATION.” The result of the joining and mapping functionality 508may be a single document 514 (e.g., an XML document) that comprises oneor more tasks that match the formal input schema for an adapter 518. Inaddition to joining and mapping, this process may involve the use offilters 512 that limit the tasks and task data produced (e.g., do notsend an invoice to customers who are being charged less than one dollar)and custom transforms 516 specified at design time that add anextensible and customizable mechanism to manipulate the task parametersprior to submission to the adapter (e.g., custom transformations mayinclude almost any transformation or manipulation of the data thatcannot be handled by either the joining itself or the filtering).

The joining and mapping functionality 508, the filters 512, and thecustom transforms 516 may all be implemented in one or moretransformation engines 134 of the supporting architecture 132 describedwith respect to FIG. 1. In general, during transformation, the data(e.g., XML data) from the formal input document 514 is broken down asjob and task parameters and passed to the adapter 518 for processing. Inthis way, the adapter 518 has all the information it needs to performthe task passed to it. In some embodiments, the adapter is designed tobe product-agnostic.

As illustrated in FIG. 6 after processing by the adapter 518, theworkflow facility may collect task and job results (602, 604, and 606),and reassemble these resources into a single output document reassembly608 (e.g., XML document). The single output document reassembly 608 mayalso incorporate information retrieved from one or more workflow designfiles 610. In some embodiments, not all tasks may result in the creationof output or results that is re-associated with the facility. However,in the illustrated embodiment, portions of the results are automaticallyextracted and persisted in a workflow storage system 614. Acorresponding identifier may replace the actual content in a result 612prior to storing.

In some instances, additional data may be associated with each taskresult even though the additional data may not be a part of the formalinput or output schema of the adapter 518. For example, it may bedesirable that each task result contain a unique identifier (e.g.InvoiceID) associated with the task result. The additional input may bepart of the input document 502 used in the joining and mappingfunctionality 508. However, the formal output schema for the adapter maynot contain this information. For example, if the output is an emailreport on users and invoices, that report may not contain an identifyingkey for the collection of documents as one of its fields. An output'sidentifying key may also be omitted in PDF or word processor filescreated to archive the reports. However, that additional data may beneeded by the workflow application to track the data collection as awhole and to make sure that output of the adapter can be related back tothe data collection by subsequent workflow tasks or to ensure that thesystem may later audit the performance of the workflow task. As part ofthe document reassembly 608, additional data not passed to the adaptermay be recombined with the results and thus referenced at a later pointin the workflow. This may be accomplished by associating the additionaldata with a unique identifier that will be output from the adapter inthe task result.

IV. System Flows

FIGS. 7 through 9 are representative flow diagrams that show processesthat occur within the system of FIGS. 1-3. These flow diagrams do notshow all functions or exchanges of data but, instead, provide anunderstanding of commands and data exchanged under the system. Thoseskilled in the relevant art will recognize that some functions orexchanges of commands and data may be repeated, varied, omitted, orsupplemented, and other aspects not shown may be readily implemented.For example, while not described in detail, a message containing datamay be transmitted through a message queue, over HTTP, etc.

FIG. 7 is a flow diagram showing a high-level vector-based workflowroutine 700 performed at the workflow facility. The routine 700 isassociated with a runtime environment in which the workflow facilityexecutes a previously designed workflow model. In this example, theworkflow model includes a series of linked steps or tasks that relate toa higher-level process. While the workflow facility does not requirethat all of the steps/tasks of an executed workflow model be automated,in the illustrated example, at least some of the steps or tasks of theworkflow model are performed via some level of automated support fromthe workflow facility.

The routine 700 assumes that a particular step associated with theworkflow model is ready to be performed, with the workflow facilityplaying a role in the performance of the step, so that the step can beperformed automatically (or at least partially automatically). Anexample of such a step is a step to send an email to a group ofcustomers. At block 701, the routine 700 reads a first collection ofinput records that is identified by the workflow model as being neededto performing the step from the workflow model. An example of such aninput is a collection of records containing email information for theindividual customers from the group of customers. The routine 700 readsthe input records as a single unit of input (as opposed to one record ata time). In this way, pre-processing of the input information isminimized, despite the routine 700 being configured to handle a widevariety of input types, including collections of records that haverecords of more than one data format or data shape.

At block 702, the routine 700 applies, to all records in the collectionof records, a function related to performing the step associated withthe workflow model. A breakdown of block 702 (e.g., as performed by aworkflow action associated with the workflow facility) is provided withrespect to FIG. 8. An example of a function related to performing a stepassociated with a workflow model is a function used to generate an emailfor individual customers identified using a collection of records. Atblock 703, the routine 700 generates output resulting from applying theappropriate function to the collection of records (e.g., the routine 700generates one or more documents containing a modified version of thecollection of records). At decision block 704, the routine 700determines whether additional functions relating to performing the stepneed to be applied to the record collection. If no further functionsneed to be applied, the routine 700 continues at block 705. However, ifat decision block 704, further functions need to be applied, the routine700 loops back to block 702 to apply the next function to all records inthe collection of records. For example, the next function applied to therecords in the collection of records may be a send email function, whichsends out the emails generated by the first function. Tasks may alsohave multiple custom actions associated with them, and the program willloop through a task until all custom actions are completed.

At decision block 705, the routine 700 checks to see whether there areadditional input units (e.g., collections of records) that need to beprocessed in association with performing the step from the workflowmodel. If so, the routine 700 loops back to block 701 to read the nextcollection of input records. If there are no further input units thatneed to be processed in association with performing the step from theworkflow model, the routine 700 ends.

FIG. 8 is a flow diagram showing a routine 800 performed by a workflowaction utilizing vector-based data inputs to complete a step in aworkflow model. The routine 800 provides details for one exampleimplementation of applying a function to a collection of records (block702) of the routine 700 of FIG. 7. In some embodiments, the routine 800is performed by a workflow action that runs in the workflow facilityenvironment, such as the workflow action 202 of FIG. 2. This workflowaction corresponds to a particular function associated with completingthe step from the workflow model. Only a single invocation of theworkflow action is needed to operate on an entire collection of records.

At block 801, the routine 800 invokes the workflow action via receipt ofinstructions to perform a workflow step. At block 802 the routine 800accesses the vector-based input (e.g., after it has been read by theworkflow facility as a collection of records, as described in block 701of FIG. 7). At block 803 the routine 800 generates a call to an adapteror adapter group (such as the adapter(s) 204 of FIG. 2). This callincludes a job request. The job request corresponds to a step associatedwith the workflow model, or alternatively, with a sub-step (e.g.,function) associated with the step from the workflow model. The jobrequest can be broken down into tasks (e.g., one task request for eachrecord in the collection of records accessed at block 802). Thus, thejob request is comprised of multiple task requests. The adapter oradapter group that is the subject of the call is configured forspecialized processing to efficiently complete the job request (on atask-by-task basis) so that the function associated with the step fromthe workflow model can be completed. Additional details of how theadapter or adapter group performs job/task processing are provided withrespect to FIG. 9. At block 804, the routine 800 obtains a compiledresult for the job request from the adapter or adapter group. Thisinformation can then be used in association with completing (or provingcompletion) of the workflow model step. The routine 800 then ends.

FIG. 9 is a flow diagram showing a routine 900 performed by an adaptermodule (or group of adapter modules) in performing processing inassociation with vector-based data inputs used to complete a step in aworkflow model. At block 901 the routine 900 receives a call from aworkflow action, such as a call generated in block 803 of the routine800 of FIG. 8). This call includes a job request (comprising multipletask requests, with each task request being associated with at least onerecord from a collection of records). At block 902, the routine 900stores the job request and the task requests information received in thecall of block 901 in an adapter database or other data store. At block903, the routine 900 retrieves, from the adapter database, parametersfor performing the next task. In reference to components of FIG. 2,blocks 901-903 may be performed by the connector proxy/data handler 212of the adapter module.

At block 904, the routine 900 performs processing for the next task. Atblock 905, the routine 900 stores the results from the processing of thetask in the adapter database or other data store. In reference tocomponents of FIG. 2, the processing may be performed by the deviceconnector/data processor 214 of the adapter. At decision block 906, theroutine 900 checks to see whether the job includes additional tasks,which may be a function performed by the connector proxy/data handler212 of FIG. 2. If there are additional tasks associated with the job,the routine 900 loops back to block 903 to retrieve, from the adapterdatabase, the parameters for the next task. However, if there are nofurther tasks associated with the job, the routine 900 continues atblock 907, where the routine 900 retrieves all the stored task resultsfrom the adapter database. At block 908, the routine 900 compiles theretrieved task results to generate a job result for the job request. Atblock 909, the routine 900 provides the compiled job result to theworkflow action, as described with respect to block 804 of the routine800 of FIG. 8. As with blocks 901-903, blocks 905-909 may be performedby the connector proxy/data handler 212 of the adapter module.

V. Conclusion

Unless the context clearly requires otherwise, throughout thedescription and the claims, the words “comprise,” “comprising,” and thelike are to be construed in an inclusive sense as opposed to anexclusive or exhaustive sense; that is to say, in the sense of“including, but not limited to.” Additionally, the words “herein,”“above,” “below” and words of similar import, when used in thisapplication, shall refer to this application as a whole and not to anyparticular portions of this application. When the claims use the word“or” in reference to a list of two or more items, that word covers allof the following interpretations of the word: any of the items in thelist, all of the items in the list, and any combination of the items inthe list.

The above Detailed Description of embodiments of the invention is notintended to be exhaustive or to limit the invention to the precise formdisclosed above. While specific embodiments of, and examples for, theinvention are described above for illustrative purposes, variousequivalent modifications are possible within the scope of the invention,as those skilled in the relevant art will recognize. For example, whileprocesses or blocks are presented in a given order, alternativeembodiments may perform routines having steps, or employ systems havingblocks, in a different order, and some processes or blocks may bedeleted, moved, added, subdivided, combined, and/or modified. Each ofthese processes or blocks may be implemented in a variety of differentways. Also, while processes or blocks are at times shown as beingperformed in series, these processes or blocks may instead be performedin parallel, or may be performed at different times. Where the contextpermits, words in the above Detailed Description using the singular orplural number may also include the plural or singular number,respectively.

The teachings of the invention provided herein can be applied to othersystems, not necessarily the system described herein. The elements andacts of the various embodiments described above can be combined toprovide further embodiments.

This application is related to commonly owned U.S. patent applicationSer. No. 10/938,396, filed Sep. 10, 2004, abandoned, entitled “CUSTOMAND CUSTOMIZABLE COMPONENTS, SUCH AS FOR WORK FLOW APPLICATIONS”;commonly owned U.S. patent application Ser. No. 11/486,397, filed Jul.12, 2006, entitled “COMPLEX DATA MERGING, SUCH AS IN A WORKFLOWAPPLICATION”; and commonly owned U.S. patent application Ser. No.10/938,118, filed Sep. 10, 2004, pending, entitled “USER-FRIENDLY DATABINDING, SUCH AS DRAG-AND-DROP DATA BINDING IN A WORKFLOW APPLICATION.”All of the above patents and applications and other references,including any that may be listed in accompanying filing papers, areincorporated herein by reference. Aspects of the invention can bemodified, if necessary, to employ the systems, functions, and conceptsof the various references described above to provide yet furtherembodiments of the invention.

These and other changes can be made to the invention in light of theabove Detailed Description. While the above description details certainembodiments of the invention and describes the best mode contemplated,no matter how detailed the above description appears in text, theinvention can be practiced in many ways. Details of the vector-basedrecord handling techniques and associated workflow facility may varyconsiderably in their implementation details, while still be encompassedby the invention disclosed herein. As noted above, particularterminology used when describing certain features or aspects of theinvention should not be taken to imply that the terminology is beingre-defined herein to be restricted to any specific characteristics,features, or aspects of the invention with which that terminology isassociated. In general, the terms used in the following claims shouldnot be construed to limit the invention to the specific embodimentsdisclosed in the specification, unless the above Detailed Descriptionsection explicitly defines such terms. Accordingly, the actual scope ofthe invention encompasses not only the disclosed embodiments, but alsoall equivalent ways of practicing or implementing the invention underthe claims.

While certain aspects of the invention are presented below in certainclaim forms, the inventors contemplate the various aspects of theinvention in any number of claim forms. For example, while only oneaspect of the invention is recited as embodied in a computer-readablemedium, other aspects may likewise be embodied in a computer-readablemedium. Accordingly, the inventors reserve the right to add additionalclaims after filing the application to pursue such additional claimforms for other aspects of the invention.

What is claimed is:
 1. A method of processing a flow of information,comprising: capturing, by a computer having a processor and a memory,information for use by a workflow system, the information comprisinginternal content that is internal to the workflow system and externalcontent that is external to the workflow system; analyzing the internalcontent and the external content to determine metadata parameters forthe captured information; associating the captured information with aprocess based at least in part on the metadata parameters; processingthe captured information in accordance with the process associatedtherewith to thereby produce output data; formatting the output datainto formatted output that conforms to an external systemcommunicatively connected to the computer, the external system havingfidelity and quality requirements for a delivery method; and deliveringthe formatted output to a recipient using the delivery method.
 2. Themethod according to claim 1, wherein the capturing comprises identifyingthe information from an application executing on a devicecommunicatively connected to the computer over a network connection,said application including a display to represent the internal contentand the external content and permit selection of portions of theinternal content and the external content, said application furtherenabling input of at least a portion of the metadata parameters toassist in said analyzing.
 3. The method according to claim 1, whereinthe capturing comprises, in one operation, capturing information fromcollections of the internal content and collections of the externalcontent such that as part of said one operation, repeatable processingis performed on the captured information based on the determinedmetadata parameters.
 4. The method according to claim 1, wherein theanalyzing the internal content and the external content comprisesidentifying relationships among a plurality of input components havingcontents to be merged.
 5. The method according to claim 1, wherein theformatting the output data comprises applying, by a delivery rulesengine, one or more delivery rules specifying the fidelity and qualityrequirements of the external system for the delivery method.
 6. Themethod according to claim 1, wherein the process comprises executing aworkflow model.
 7. The method according to claim 1, wherein thedelivering comprises making a simultaneous multi-channel delivery.
 8. Acomputer program product comprising at least one non-transitory computerreadable medium storing instructions translatable by a computer toperform: capturing information for use by a workflow system, theinformation comprising internal content that is internal to the workflowsystem and external content that is external to the workflow system;analyzing the internal content and the external content to determinemetadata parameters for the captured information; associating thecaptured information with a process based at least in part on themetadata parameters; processing the captured information in accordancewith the process associated therewith to thereby produce output data;formatting the output data into formatted output that conforms to anexternal system communicatively connected to the computer, the externalsystem having fidelity and quality requirements for a delivery method;and delivering the formatted output to a recipient using the deliverymethod.
 9. The computer program product of claim 8, wherein thecapturing comprises identifying the information from an applicationexecuting on a device communicatively connected to the computer over anetwork connection, said application including a display to representthe internal content and the external content and permit selection ofportions of the internal content and the external content, saidapplication further enabling input of at least a portion of the metadataparameters to assist in said analyzing.
 10. The computer program productof claim 8, wherein the capturing comprises, in one operation, capturinginformation from collections of the internal content and collections ofthe external content such that as part of said one operation, repeatableprocessing is performed on the captured information based on thedetermined metadata parameters.
 11. The computer program product ofclaim 8, wherein the analyzing the internal content and the externalcontent comprises identifying relationships among a plurality of inputcomponents having contents to be merged.
 12. The computer programproduct of claim 8, wherein the formatting the output data comprisesapplying, by a delivery rules engine, one or more delivery rulesspecifying the fidelity and quality requirements of the external systemfor the delivery method.
 13. The computer program product of claim 8,wherein the process comprises executing a workflow model.
 14. Thecomputer program product of claim 8, wherein the delivering comprisesmaking a simultaneous multi-channel delivery.
 15. A system forprocessing a flow of information, comprising: at least one processor; atleast one non-transitory computer readable medium storing instructionstranslatable by the at least one processor to perform: capturinginformation for use by a workflow system, the information comprisinginternal content that is internal to the workflow system and externalcontent that is external to the workflow system; analyzing the internalcontent and the external content to determine metadata parameters forthe captured information; associating the captured information with aprocess based at least in part on the metadata parameters; processingthe captured information in accordance with the process associatedtherewith to thereby produce output data; formatting the output datainto formatted output that conforms to an external systemcommunicatively connected to the system, the external system havingfidelity and quality requirements for a delivery method; and deliveringthe formatted output to a recipient using the delivery method.
 16. Thesystem of claim 15, wherein the capturing comprises identifying theinformation from an application executing on a device communicativelyconnected to the system over a network connection, said applicationincluding a display to represent the internal content and the externalcontent and permit selection of portions of the internal content and theexternal content, said application further enabling input of at least aportion of the metadata parameters to assist in said analyzing.
 17. Thesystem of claim 15, wherein the capturing comprises, in one operation,capturing information from collections of the internal content andcollections of the external content such that as part of said oneoperation, repeatable processing is performed on the capturedinformation based on the determined metadata parameters
 18. The systemof claim 15, wherein the analyzing the internal content and the externalcontent comprises identifying relationships among a plurality of inputcomponents having contents to be merged.
 19. The system of claim 15,wherein the formatting the output data comprises applying, by a deliveryrules engine, one or more delivery rules specifying the fidelity andquality requirements of the external system for the delivery method. 20.The system of claim 15, wherein the process comprises executing aworkflow model.